Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation - Emmanuel Bengio; Moksh Jain; Maksym Korablyov; Doina Precup; Yoshua Bengio (Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, NeurIPS 2021, December 6-14, 2021, virtual, 2021)

Exploring the Wasserstein metric for time-to-event analysis - Tristan Sylvain; Margaux Luck; Joseph Paul Cohen; Héloïse Cardinal; Andrea Lodi; Yoshua Bengio (Proceedings of AAAI Symposium on Survival Prediction - Algorithms, Challenges and Applications, SPACA 2021, Stanford University, Palo Alto, CA, USA, March 22-24, 2021, 2021)

Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing its Gradient Estimator Bias - Axel Laborieux; Maxence Ernoult; Benjamin Scellier; Yoshua Bengio; Julie Grollier; Damien Querlioz (CoRR, 2021)

Structured Sparsity Inducing Adaptive Optimizers for Deep Learning - Tristan Deleu; Yoshua Bengio (CoRR, 2021)

DEUP: Direct Epistemic Uncertainty Prediction - Moksh Jain; Salem Lahlou; Hadi Nekoei; Victor Butoi; Paul Bertin; Jarrid Rector-Brooks; Maksym Korablyov; Yoshua Bengio (CoRR, 2021)

Learning Neural Generative Dynamics for Molecular Conformation Generation - Minkai Xu; Shitong Luo; Yoshua Bengio; Jian Peng; Jian Tang (CoRR, 2021)

Towards Causal Representation Learning - Bernhard Schölkopf; Francesco Locatello; Stefan Bauer; Nan Rosemary Ke; Nal Kalchbrenner; Anirudh Goyal; Yoshua Bengio (CoRR, 2021)

Transformers with Competitive Ensembles of Independent Mechanisms - Alex Lamb; Di He; Anirudh Goyal; Guolin Ke; Chien-Feng Liao; Mirco Ravanelli; Yoshua Bengio (CoRR, 2021)

Coordination Among Neural Modules Through a Shared Global Workspace - Anirudh Goyal; Aniket Didolkar; Alex Lamb; Kartikeya Badola; Nan Rosemary Ke; Nasim Rahaman; Jonathan Binas; Charles Blundell; Michael Mozer; Yoshua Bengio (CoRR, 2021)

Neural Production Systems - Anirudh Goyal; Aniket Didolkar; Nan Rosemary Ke; Charles Blundell; Philippe Beaudoin; Nicolas Heess; Michael Mozer; Yoshua Bengio (CoRR, 2021)

hBert + BiasCorp - Fighting Racism on the Web - Olawale Onabola; Zhuang Ma; Yang Xie; Benjamin Akera; Abdulrahman Ibraheem; Jia Xue; Dianbo Liu; Yoshua Bengio (CoRR, 2021)

Comparative Study of Learning Outcomes for Online Learning Platforms - François St-Hilaire; Nathan Burns; Robert Belfer; Muhammad Shayan; Ariella Smofsky; Dung Do Vu; Antoine Frau; Joseph Potochny; Farid Faraji; Vincent Pavero; Neroli Ko; Ansona Onyi Ching; et al. (CoRR, 2021)

An End-to-End Framework for Molecular Conformation Generation via Bilevel Programming - Minkai Xu; Wujie Wang; Shitong Luo; Chence Shi; Yoshua Bengio; Rafael Gómez-Bombarelli; Jian Tang (CoRR, 2021)

Fast and Slow Learning of Recurrent Independent Mechanisms - Kanika Madan; Nan Rosemary Ke; Anirudh Goyal; Bernhard Schölkopf; Yoshua Bengio (CoRR, 2021)

A Consciousness-Inspired Planning Agent for Model-Based Reinforcement Learning - Mingde Zhao; Zhen Liu; Sitao Luan; Shuyuan Zhang; Doina Precup; Yoshua Bengio (CoRR, 2021)

Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation - Emmanuel Bengio; Moksh Jain; Maksym Korablyov; Doina Precup; Yoshua Bengio (CoRR, 2021)

SpeechBrain: A General-Purpose Speech Toolkit - Mirco Ravanelli; Titouan Parcollet; Peter Plantinga; Aku Rouhe; Samuele Cornell; Loren Lugosch; Cem Subakan; Nauman Dawalatabad; Abdelwahab Heba; Jianyuan Zhong; Ju-Chieh Chou; Sung-Lin Yeh; et al. (CoRR, 2021)

Invariance Principle Meets Information Bottleneck for Out-of-Distribution Generalization - Kartik Ahuja; Ethan Caballero; Dinghuai Zhang; Yoshua Bengio; Ioannis Mitliagkas; Irina Rish (CoRR, 2021)

Variational Causal Networks: Approximate Bayesian Inference over Causal Structures - Yashas Annadani; Jonas Rothfuss; Alexandre Lacoste; Nino Scherrer; Anirudh Goyal; Yoshua Bengio; Stefan Bauer (CoRR, 2021)

Predicting Unreliable Predictions by Shattering a Neural Network - Xu Ji; Razvan Pascanu; R. Devon Hjelm; Andrea Vedaldi; Balaji Lakshminarayanan; Yoshua Bengio (CoRR, 2021)

The Causal-Neural Connection: Expressiveness, Learnability, and Inference - Kevin Xia; Kai-Zhan Lee; Yoshua Bengio; Elias Bareinboim (CoRR, 2021)

Systematic Evaluation of Causal Discovery in Visual Model Based Reinforcement Learning - Nan Rosemary Ke; Aniket Didolkar; Sarthak Mittal; Anirudh Goyal; Guillaume Lajoie; Stefan Bauer; Danilo J. Rezende; Yoshua Bengio; Michael Mozer; Christopher J. Pal (CoRR, 2021)

Discrete-Valued Neural Communication - Dianbo Liu; Alex Lamb; Kenji Kawaguchi; Anirudh Goyal; Chen Sun; Michael Curtis Mozer; Yoshua Bengio (CoRR, 2021)

Learning Neural Causal Models with Active Interventions - Nino Scherrer; Olexa Bilaniuk; Yashas Annadani; Anirudh Goyal; Patrick Schwab; Bernhard Schölkopf; Michael C. Mozer; Yoshua Bengio; Stefan Bauer; Nan Rosemary Ke (CoRR, 2021)

ClimateGAN: Raising Climate Change Awareness by Generating Images of Floods - Victor Schmidt; Alexandra Sasha Luccioni; Mélisande Teng; Tianyu Zhang; Alexia Reynaud; Sunand Raghupathi; Gautier Cosne; Adrien Juraver; Vahe Vardanyan; Alex Hernández-García; Yoshua Bengio (CoRR, 2021)

Unifying Likelihood-free Inference with Black-box Sequence Design and Beyond - Dinghuai Zhang; Jie Fu; Yoshua Bengio; Aaron C. Courville (CoRR, 2021)

Dynamic Inference with Neural Interpreters - Nasim Rahaman; Muhammad Waleed Gondal; Shruti Joshi; Peter V. Gehler; Yoshua Bengio; Francesco Locatello; Bernhard Schölkopf (CoRR, 2021)

Graph Neural Networks with Learnable Structural and Positional Representations - Vijay Prakash Dwivedi; Anh Tuan Luu; Thomas Laurent; Yoshua Bengio; Xavier Bresson (CoRR, 2021)

Compositional Attention: Disentangling Search and Retrieval - Sarthak Mittal; Sharath Chandra Raparthy; Irina Rish; Yoshua Bengio; Guillaume Lajoie (CoRR, 2021)

Chunked Autoregressive GAN for Conditional Waveform Synthesis - Max Morrison; Rithesh Kumar; Kundan Kumar; Prem Seetharaman; Aaron C. Courville; Yoshua Bengio (CoRR, 2021)

From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence - Nicholas Roy; Ingmar Posner; Tim D. Barfoot; Philippe Beaudoin; Yoshua Bengio; Jeannette Bohg; Oliver Brock; Isabelle Depatie; Dieter Fox; Daniel E. Koditschek; Tomás Lozano-Pérez; Vikash Mansinghka; et al. (CoRR, 2021)

Properties from Mechanisms: An Equivariance Perspective on Identifiable Representation Learning - Kartik Ahuja; Jason S. Hartford; Yoshua Bengio (CoRR, 2021)

GFlowNet Foundations - Yoshua Bengio; Tristan Deleu; Edward J. Hu; Salem Lahlou; Mo Tiwari; Emmanuel Bengio (CoRR, 2021)

Multi-scale Feature Learning Dynamics: Insights for Double Descent - Mohammad Pezeshki; Amartya Mitra; Yoshua Bengio; Guillaume Lajoie (CoRR, 2021)

Multi-Domain Balanced Sampling Improves Out-of-Distribution Generalization of Chest X-ray Pathology Prediction Models - Enoch Tetteh; Joseph D. Viviano; Yoshua Bengio; David Krueger; Joseph Paul Cohen (CoRR, 2021)

Joint Learning of Generative Translator and Classifier for Visually Similar Classes - ByungIn Yoo; Tristan Sylvain; Yoshua Bengio; Junmo Kim (IEEE Access, 2020)

Factorized embeddings learns rich and biologically meaningful embedding spaces using factorized tensor decomposition - Assya Trofimov; Joseph Paul Cohen; Yoshua Bengio; Claude Perreault; Sébastien Lemieux (Bioinform., 2020)

Generative adversarial networks - Ian J. Goodfellow; Jean Pouget-Abadie; Mehdi Mirza; Bing Xu; David Warde-Farley; Sherjil Ozair; Aaron C. Courville; Yoshua Bengio (Commun. ACM, 2020)

The Bottleneck Simulator: A Model-Based Deep Reinforcement Learning Approach - Iulian Vlad Serban; Chinnadhurai Sankar; Michael Pieper; Joelle Pineau; Yoshua Bengio (J. Artif. Intell. Res., 2020)

Establishing an evaluation metric to quantify climate change image realism - Sharon Zhou; Alexandra Luccioni; Gautier Cosne; Michael S. Bernstein; Yoshua Bengio (Mach. Learn. Sci. Technol., 2020)

Toward Training Recurrent Neural Networks for Lifelong Learning - Shagun Sodhani; Sarath Chandar; Yoshua Bengio (Neural Comput., 2020)

On the Morality of Artificial Intelligence [Commentary] - Alexandra Luccioni; Yoshua Bengio (IEEE Technol. Soc. Mag., 2020)

Combating False Negatives in Adversarial Imitation Learning (Student Abstract) - Konrad Zolna; Chitwan Saharia; Léonard Boussioux; David Yu-Tung Hui; Maxime Chevalier-Boisvert; Dzmitry Bahdanau; Yoshua Bengio (The Thirty-Fourth AAAI Conference on Artificial Intelligence, AAAI 2020, The Thirty-Second Innovative Applications of Artificial Intelligence Conference, IAAI 2020, The Tenth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2020, New York, NY, USA, February 7-12, 2020, 2020)

Compositional Generalization by Factorizing Alignment and Translation - Jacob L. Russin; Jason Jo; Randall C. O'Reilly; Yoshua Bengio (Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop, ACL 2020, Online, July 5-10, 2020, 2020)

Exploiting Syntactic Structure for Better Language Modeling: A Syntactic Distance Approach - Wenyu Du; Zhouhan Lin; Yikang Shen; Timothy J. O'Donnell; Yoshua Bengio; Yue Zhang (Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, ACL 2020, Online, July 5-10, 2020, 2020)

A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM - Iulian Vlad Serban; Varun Gupta; Ekaterina Kochmar; Dung Do Vu; Robert Belfer; Joelle Pineau; Aaron C. Courville; Laurent Charlin; Yoshua Bengio (Artificial Intelligence in Education - 21st International Conference, AIED 2020, Ifrane, Morocco, July 6-10, 2020, Proceedings, Part II, 2020)

On the interplay between noise and curvature and its effect on optimization and generalization - Valentin Thomas; Fabian Pedregosa; Bart van Merriënboer; Pierre-Antoine Manzagol; Yoshua Bengio; Nicolas Le Roux (The 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26-28 August 2020, Online [Palermo, Sicily, Italy], 2020)

Systematicity in a Recurrent Neural Network by Factorizing Syntax and Semantics - Jacob L. Russin; Jason Jo; Randall C. O'Reilly; Yoshua Bengio (Proceedings of the 42th Annual Meeting of the Cognitive Science Society - Developing a Mind: Learning in Humans, Animals, and Machines, CogSci 2020, virtual, July 29 - August 1, 2020, 2020)

A Learning-Based Algorithm to Quickly Compute Good Primal Solutions for Stochastic Integer Programs - Yoshua Bengio; Emma Frejinger; Andrea Lodi; Rahul Patel; Sriram Sankaranarayanan (Integration of Constraint Programming, Artificial Intelligence, and Operations Research - 17th International Conference, CPAIOR 2020, Vienna, Austria, September 21-24, 2020, Proceedings, 2020)

Multi-Image Super-Resolution for Remote Sensing using Deep Recurrent Networks - Md Rifat Arefin; Vincent Michalski; Pierre-Luc St-Charles; Alfredo Kalaitzis; Sookyung Kim; Samira Ebrahimi Kahou; Yoshua Bengio (2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR Workshops 2020, Seattle, WA, USA, June 14-19, 2020, 2020)

DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning - Timo Milbich; Karsten Roth; Homanga Bharadhwaj; Samarth Sinha; Yoshua Bengio; Björn Ommer; Joseph Paul Cohen (Computer Vision - ECCV 2020 - 16th European Conference, Glasgow, UK, August 23-28, 2020, Proceedings, Part VIII, 2020)

Experience Grounds Language - Yonatan Bisk; Ari Holtzman; Jesse Thomason; Jacob Andreas; Yoshua Bengio; Joyce Chai; Mirella Lapata; Angeliki Lazaridou; Jonathan May; Aleksandr Nisnevich; Nicolas Pinto; Joseph P. Turian (Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, EMNLP 2020, Online, November 16-20, 2020, 2020)

Multi-Task Self-Supervised Learning for Robust Speech Recognition - Mirco Ravanelli; Jianyuan Zhong; Santiago Pascual; Pawel Swietojanski; João Monteiro; Jan Trmal; Yoshua Bengio (2020 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2020, Barcelona, Spain, May 4-8, 2020, 2020)

A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms - Yoshua Bengio; Tristan Deleu; Nasim Rahaman; Nan Rosemary Ke; Sébastien Lachapelle; Olexa Bilaniuk; Anirudh Goyal; Christopher J. Pal (8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020, 2020)

The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget - Anirudh Goyal; Yoshua Bengio; Matthew M. Botvinick; Sergey Levine (8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020, 2020)

Reinforcement Learning with Competitive Ensembles of Information-Constrained Primitives - Anirudh Goyal; Shagun Sodhani; Jonathan Binas; Xue Bin Peng; Sergey Levine; Yoshua Bengio (8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020, 2020)

N-BEATS: Neural basis expansion analysis for interpretable time series forecasting - Boris N. Oreshkin; Dmitri Carpov; Nicolas Chapados; Yoshua Bengio (8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020, 2020)

Learning the Arrow of Time for Problems in Reinforcement Learning - Nasim Rahaman; Steffen Wolf; Anirudh Goyal; Roman Remme; Yoshua Bengio (8th International Conference on Learning Representations, ICLR 2020, Addis Ababa, Ethiopia, April 26-30, 2020, 2020)

Revisiting Fundamentals of Experience Replay - William Fedus; Prajit Ramachandran; Rishabh Agarwal; Yoshua Bengio; Hugo Larochelle; Mark Rowland; Will Dabney (Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, 2020)

Learning to Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning - Sai Krishna Gottipati; Boris Sattarov; Sufeng Niu; Yashaswi Pathak; Haoran Wei; Shengchao Liu; Simon Blackburn; Karam M. J. Thomas; Connor W. Coley; Jian Tang; Sarath Chandar; Yoshua Bengio (Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, 2020)

Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules - Sarthak Mittal; Alex Lamb; Anirudh Goyal; Vikram Voleti; Murray Shanahan; Guillaume Lajoie; Michael Mozer; Yoshua Bengio (Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, 2020)

Small-GAN: Speeding up GAN Training using Core-Sets - Samarth Sinha; Han Zhang; Anirudh Goyal; Yoshua Bengio; Hugo Larochelle; Augustus Odena (Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, 2020)

Perceptual Generative Autoencoders - Zijun Zhang; Ruixiang Zhang; Zongpeng Li; Yoshua Bengio; Liam Paull (Proceedings of the 37th International Conference on Machine Learning, ICML 2020, 13-18 July 2020, Virtual Event, 2020)

Attention Based Pruning for Shift Networks - Ghouthi Boukli Hacene; Carlos Lassance; Vincent Gripon; Matthieu Courbariaux; Yoshua Bengio (25th International Conference on Pattern Recognition, ICPR 2020, Virtual Event / Milan, Italy, January 10-15, 2021, 2020)

Quantized Guided Pruning for Efficient Hardware Implementations of Deep Neural Networks - Ghouthi Boukli Hacene; Vincent Gripon; Matthieu Arzel; Nicolas Farrugia; Yoshua Bengio (18th IEEE International New Circuits and Systems Conference, NEWCAS 2020, Montréal, QC, Canada, June 16-19, 2020, 2020)

Your GAN is Secretly an Energy-based Model and You Should Use Discriminator Driven Latent Sampling - Tong Che; Ruixiang Zhang; Jascha Sohl-Dickstein; Hugo Larochelle; Liam Paull; Yuan Cao; Yoshua Bengio (Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020)

Hybrid Models for Learning to Branch - Prateek Gupta; Maxime Gasse; Elias B. Khalil; Pawan Kumar Mudigonda; Andrea Lodi; Yoshua Bengio (Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020)

Untangling tradeoffs between recurrence and self-attention in artificial neural networks - Giancarlo Kerg; Bhargav Kanuparthi; Anirudh Goyal; Kyle Goyette; Yoshua Bengio; Guillaume Lajoie (Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, NeurIPS 2020, December 6-12, 2020, virtual, 2020)

Learning from Learning Machines: Optimisation, Rules, and Social Norms - Travis LaCroix; Yoshua Bengio (CoRR, 2020)

Universal Successor Features for Transfer Reinforcement Learning - Chen Ma; Dylan R. Ashley; Junfeng Wen; Yoshua Bengio (CoRR, 2020)

Multi-task self-supervised learning for Robust Speech Recognition - Mirco Ravanelli; Jianyuan Zhong; Santiago Pascual; Pawel Swietojanski; João Monteiro; Jan Trmal; Yoshua Bengio (CoRR, 2020)

Using Simulated Data to Generate Images of Climate Change - Gautier Cosne; Adrien Juraver; Mélisande Teng; Victor Schmidt; Vahe Vardanyan; Alexandra Luccioni; Yoshua Bengio (CoRR, 2020)

Combating False Negatives in Adversarial Imitation Learning - Konrad Zolna; Chitwan Saharia; Léonard Boussioux; David Yu-Tung Hui; Maxime Chevalier-Boisvert; Dzmitry Bahdanau; Yoshua Bengio (CoRR, 2020)

Meta-learning framework with applications to zero-shot time-series forecasting - Boris N. Oreshkin; Dmitri Carpov; Nicolas Chapados; Yoshua Bengio (CoRR, 2020)

BitPruning: Learning Bitlengths for Aggressive and Accurate Quantization - Milos Nikolic; Ghouthi Boukli Hacene; Ciaran Bannon; Alberto Delmas Lascorz; Matthieu Courbariaux; Yoshua Bengio; Vincent Gripon; Andreas Moshovos (CoRR, 2020)

Parameterizing Branch-and-Bound Search Trees to Learn Branching Policies - Giulia Zarpellon; Jason Jo; Andrea Lodi; Yoshua Bengio (CoRR, 2020)

HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagery - Michel Deudon; Alfredo Kalaitzis; Israel Goytom; Md Rifat Arefin; Zhichao Lin; Kris Sankaran; Vincent Michalski; Samira Ebrahimi Kahou; Julien Cornebise; Yoshua Bengio (CoRR, 2020)

Neural Bayes: A Generic Parameterization Method for Unsupervised Representation Learning - Devansh Arpit; Huan Wang; Caiming Xiong; Richard Socher; Yoshua Bengio (CoRR, 2020)

On Catastrophic Interference in Atari 2600 Games - William Fedus; Dibya Ghosh; John D. Martin; Marc G. Bellemare; Yoshua Bengio; Hugo Larochelle (CoRR, 2020)

Benchmarking Graph Neural Networks - Vijay Prakash Dwivedi; Chaitanya K. Joshi; Thomas Laurent; Yoshua Bengio; Xavier Bresson (CoRR, 2020)

Continuous Domain Adaptation with Variational Domain-Agnostic Feature Replay - Qicheng Lao; Xiang Jiang; Mohammad Havaei; Yoshua Bengio (CoRR, 2020)

Your GAN is Secretly an Energy-based Model and You Should use Discriminator Driven Latent Sampling - Tong Che; Ruixiang Zhang; Jascha Sohl-Dickstein; Hugo Larochelle; Liam Paull; Yuan Cao; Yoshua Bengio (CoRR, 2020)

Object-Centric Image Generation from Layouts - Tristan Sylvain; Pengchuan Zhang; Yoshua Bengio; R. Devon Hjelm; Shikhar Sharma (CoRR, 2020)

Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims - Miles Brundage; Shahar Avin; Jasmine Wang; Haydn Belfield; Gretchen Krueger; Gillian K. Hadfield; Heidy Khlaaf; Jingying Yang; Helen Toner; Ruth Fong; Tegan Maharaj; Pang Wei Koh; et al. (CoRR, 2020)

Experience Grounds Language - Yonatan Bisk; Ari Holtzman; Jesse Thomason; Jacob Andreas; Yoshua Bengio; Joyce Chai; Mirella Lapata; Angeliki Lazaridou; Jonathan May; Aleksandr Nisnevich; Nicolas Pinto; Joseph P. Turian (CoRR, 2020)

The Variational Bandwidth Bottleneck: Stochastic Evaluation on an Information Budget - Anirudh Goyal; Yoshua Bengio; Matthew M. Botvinick; Sergey Levine (CoRR, 2020)

Learning To Navigate The Synthetically Accessible Chemical Space Using Reinforcement Learning - Sai Krishna Gottipati; Boris Sattarov; Sufeng Niu; Yashaswi Pathak; Haoran Wei; Shengchao Liu; Karam M. J. Thomas; Simon Blackburn; Connor W. Coley; Jian Tang; Sarath Chandar; Yoshua Bengio (CoRR, 2020)

DiVA: Diverse Visual Feature Aggregation for Deep Metric Learning - Timo Milbich; Karsten Roth; Homanga Bharadhwaj; Samarth Sinha; Yoshua Bengio; Björn Ommer; Joseph Paul Cohen (CoRR, 2020)

Equilibrium Propagation with Continual Weight Updates - Maxence Ernoult; Julie Grollier; Damien Querlioz; Yoshua Bengio; Benjamin Scellier (CoRR, 2020)

Continual Weight Updates and Convolutional Architectures for Equilibrium Propagation - Maxence Ernoult; Julie Grollier; Damien Querlioz; Yoshua Bengio; Benjamin Scellier (CoRR, 2020)

Exploiting Syntactic Structure for Better Language Modeling: A Syntactic Distance Approach - Wenyu Du; Zhouhan Lin; Yikang Shen; Timothy J. O'Donnell; Yoshua Bengio; Yue Zhang (CoRR, 2020)

A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM - Iulian Vlad Serban; Varun Gupta; Ekaterina Kochmar; Dung Do Vu; Robert Belfer; Joelle Pineau; Aaron C. Courville; Laurent Charlin; Yoshua Bengio (CoRR, 2020)

COVI White Paper - Hannah Alsdurf; Yoshua Bengio; Tristan Deleu; Prateek Gupta; Daphne Ippolito; Richard Janda; Max Jarvie; Tyler Kolody; Sekoul Krastev; Tegan Maharaj; Robert Obryk; Dan Pilat; et al. (CoRR, 2020)

An Analysis of the Adaptation Speed of Causal Models - Rémi Le Priol; Reza Babanezhad Harikandeh; Yoshua Bengio; Simon Lacoste-Julien (CoRR, 2020)

Predicting COVID-19 Pneumonia Severity on Chest X-ray with Deep Learning - Joseph Paul Cohen; Lan Dao; Paul Morrison; Karsten Roth; Yoshua Bengio; Beiyi Shen; Almas Abbasi; Mahsa Hoshmand-Kochi; Marzyeh Ghassemi; Haifang Li; Tim Q. Duong (CoRR, 2020)

Training End-to-End Analog Neural Networks with Equilibrium Propagation - Jack D. Kendall; Ross D. Pantone; Kalpana Manickavasagam; Yoshua Bengio; Benjamin Scellier (CoRR, 2020)

Scaling Equilibrium Propagation to Deep ConvNets by Drastically Reducing its Gradient Estimator Bias - Axel Laborieux; Maxence Ernoult; Benjamin Scellier; Yoshua Bengio; Julie Grollier; Damien Querlioz (CoRR, 2020)

Learning Causal Models Online - Khurram Javed; Martha White; Yoshua Bengio (CoRR, 2020)

Untangling tradeoffs between recurrence and self-attention in neural networks - Giancarlo Kerg; Bhargav Kanuparthi; Anirudh Goyal; Kyle Goyette; Yoshua Bengio; Guillaume Lajoie (CoRR, 2020)

HNHN: Hypergraph Networks with Hyperedge Neurons - Yihe Dong; Will Sawin; Yoshua Bengio (CoRR, 2020)

Image-to-image Mapping with Many Domains by Sparse Attribute Transfer - Matthew Amodio; Rim Assouel; Victor Schmidt; Tristan Sylvain; Smita Krishnaswamy; Yoshua Bengio (CoRR, 2020)

Rethinking Distributional Matching Based Domain Adaptation - Bo Li; Yezhen Wang; Tong Che; Shanghang Zhang; Sicheng Zhao; Pengfei Xu; Wei Zhou; Yoshua Bengio; Kurt Keutzer (CoRR, 2020)

Hybrid Models for Learning to Branch - Prateek Gupta; Maxime Gasse; Elias B. Khalil; M. Pawan Kumar; Andrea Lodi; Yoshua Bengio (CoRR, 2020)

Object Files and Schemata: Factorizing Declarative and Procedural Knowledge in Dynamical Systems - Anirudh Goyal; Alex Lamb; Phanideep Gampa; Philippe Beaudoin; Sergey Levine; Charles Blundell; Yoshua Bengio; Michael Mozer (CoRR, 2020)

Learning to Combine Top-Down and Bottom-Up Signals in Recurrent Neural Networks with Attention over Modules - Sarthak Mittal; Alex Lamb; Anirudh Goyal; Vikram Voleti; Murray Shanahan; Guillaume Lajoie; Michael Mozer; Yoshua Bengio (CoRR, 2020)

S2RMs: Spatially Structured Recurrent Modules - Nasim Rahaman; Anirudh Goyal; Muhammad Waleed Gondal; Manuel Wuthrich; Stefan Bauer; Yash Sharma; Yoshua Bengio; Bernhard Schölkopf (CoRR, 2020)

Revisiting Fundamentals of Experience Replay - William Fedus; Prajit Ramachandran; Rishabh Agarwal; Yoshua Bengio; Hugo Larochelle; Mark Rowland; Will Dabney (CoRR, 2020)

BabyAI 1.1 - David Yu-Tung Hui; Maxime Chevalier-Boisvert; Dzmitry Bahdanau; Yoshua Bengio (CoRR, 2020)

Deriving Differential Target Propagation from Iterating Approximate Inverses - Yoshua Bengio (CoRR, 2020)

Mastering Rate based Curriculum Learning - Lucas Willems; Salem Lahlou; Yoshua Bengio (CoRR, 2020)

Visual Concept Reasoning Networks - Taesup Kim; Sungwoong Kim; Yoshua Bengio (CoRR, 2020)

RNNLogic: Learning Logic Rules for Reasoning on Knowledge Graphs - Meng Qu; Jun-Kun Chen; Louis-Pascal A. C. Xhonneux; Yoshua Bengio; Jian Tang (CoRR, 2020)

CausalWorld: A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning - Ossama Ahmed; Frederik Träuble; Anirudh Goyal; Alexander Neitz; Manuel Wüthrich; Yoshua Bengio; Bernhard Schölkopf; Stefan Bauer (CoRR, 2020)

Neural Function Modules with Sparse Arguments: A Dynamic Approach to Integrating Information across Layers - Alex Lamb; Anirudh Goyal; Agnieszka Slowik; Michael Mozer; Philippe Beaudoin; Yoshua Bengio (CoRR, 2020)

Cross-Modal Information Maximization for Medical Imaging: CMIM - Tristan Sylvain; Francis Dutil; Tess Berthier; Lisa Di-Jorio; Margaux Luck; R. Devon Hjelm; Yoshua Bengio (CoRR, 2020)

NU-GAN: High resolution neural upsampling with GAN - Rithesh Kumar; Kundan Kumar; Vicki Anand; Yoshua Bengio; Aaron C. Courville (CoRR, 2020)

Predicting Infectiousness for Proactive Contact Tracing - Yoshua Bengio; Prateek Gupta; Tegan Maharaj; Nasim Rahaman; Martin Weiss; Tristan Deleu; Eilif B. Müller; Meng Qu; Victor Schmidt; Pierre-Luc St-Charles; Hannah Alsdurf; Olexa Bilaniuk; et al. (CoRR, 2020)

COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing - Prateek Gupta; Tegan Maharaj; Martin Weiss; Nasim Rahaman; Hannah Alsdurf; Abhinav Sharma; Nanor Minoyan; Soren Harnois-Leblanc; Victor Schmidt; Pierre-Luc St-Charles; Tristan Deleu; Andrew Williams; et al. (CoRR, 2020)

Gradient Starvation: A Learning Proclivity in Neural Networks - Mohammad Pezeshki; Sékou-Oumar Kaba; Yoshua Bengio; Aaron C. Courville; Doina Precup; Guillaume Lajoie (CoRR, 2020)

RetroGNN: Approximating Retrosynthesis by Graph Neural Networks for De Novo Drug Design - Cheng-Hao Liu; Maksym Korablyov; Stanislaw Jastrzebski; Pawel Wlodarczyk-Pruszynski; Yoshua Bengio; Marwin H. S. Segler (CoRR, 2020)

Inductive Biases for Deep Learning of Higher-Level Cognition - Anirudh Goyal; Yoshua Bengio (CoRR, 2020)

Machine Learning for Glacier Monitoring in the Hindu Kush Himalaya - Shimaa Baraka; Benjamin Akera; Bibek Aryal; Tenzing Chogyal Sherpa; Finu Shresta; Anthony Ortiz; Kris Sankaran; Juan M. Lavista Ferres; Mir Matin; Yoshua Bengio (CoRR, 2020)

Equivalence of Equilibrium Propagation and Recurrent Backpropagation - Benjamin Scellier; Yoshua Bengio (Neural Comput., 2019)

Gated Orthogonal Recurrent Units: On Learning to Forget - Li Jing; Çaglar Gülçehre; John Peurifoy; Yichen Shen; Max Tegmark; Marin Soljacic; Yoshua Bengio (Neural Comput., 2019)

Depth with nonlinearity creates no bad local minima in ResNets - Kenji Kawaguchi; Yoshua Bengio (Neural Networks, 2019)

Towards Non-Saturating Recurrent Units for Modelling Long-Term Dependencies - Sarath Chandar; Chinnadhurai Sankar; Eugene Vorontsov; Samira Ebrahimi Kahou; Yoshua Bengio (The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019, 2019)

Combined Reinforcement Learning via Abstract Representations - Vincent François-Lavet; Yoshua Bengio; Doina Precup; Joelle Pineau (The Thirty-Third AAAI Conference on Artificial Intelligence, AAAI 2019, The Thirty-First Innovative Applications of Artificial Intelligence Conference, IAAI 2019, The Ninth AAAI Symposium on Educational Advances in Artificial Intelligence, EAAI 2019, Honolulu, Hawaii, USA, January 27 - February 1, 2019, 2019)

Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study - Chinnadhurai Sankar; Sandeep Subramanian; Chris Pal; Sarath Chandar; Yoshua Bengio (Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, Florence, Italy, July 28- August 2, 2019, Volume 1: Long Papers, 2019)

Interpolated Adversarial Training: Achieving Robust Neural Networks Without Sacrificing Too Much Accuracy - Alex Lamb; Vikas Verma; Juho Kannala; Yoshua Bengio (Proceedings of the 12th ACM Workshop on Artificial Intelligence and Security, AISec@CCS 2019, London, UK, November 15, 2019, 2019)

Interactive Language Learning by Question Answering - Xingdi Yuan; Marc-Alexandre Côté; Jie Fu; Zhouhan Lin; Chris Pal; Yoshua Bengio; Adam Trischler (Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, EMNLP-IJCNLP 2019, Hong Kong, China, November 3-7, 2019, 2019)

How Transferable Are Features in Convolutional Neural Network Acoustic Models across Languages? - Jessica A. F. Thompson; Marc Schönwiesner; Yoshua Bengio; Daniel Willett (IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2019, Brighton, United Kingdom, May 12-17, 2019, 2019)

A Highly Adaptive Acoustic Model for Accurate Multi-dialect Speech Recognition - Sanghyun Yoo; Inchul Song; Yoshua Bengio (IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2019, Brighton, United Kingdom, May 12-17, 2019, 2019)

Representation Mixing for TTS Synthesis - Kyle Kastner; João Felipe Santos; Yoshua Bengio; Aaron C. Courville (IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2019, Brighton, United Kingdom, May 12-17, 2019, 2019)

The Pytorch-kaldi Speech Recognition Toolkit - Mirco Ravanelli; Titouan Parcollet; Yoshua Bengio (IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2019, Brighton, United Kingdom, May 12-17, 2019, 2019)

Learning Fixed Points in Generative Adversarial Networks: From Image-to-Image Translation to Disease Detection and Localization - Md Mahfuzur Rahman Siddiquee; Zongwei Zhou; Nima Tajbakhsh; Ruibin Feng; Michael B. Gotway; Yoshua Bengio; Jianming Liang (2019 IEEE/CVF International Conference on Computer Vision, ICCV 2019, Seoul, Korea (South), October 27 - November 2, 2019, 2019)

Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction - Alaaeldin El-Nouby; Shikhar Sharma; Hannes Schulz; R. Devon Hjelm; Layla El Asri; Samira Ebrahimi Kahou; Yoshua Bengio; Graham W. Taylor (2019 IEEE/CVF International Conference on Computer Vision, ICCV 2019, Seoul, Korea (South), October 27 - November 2, 2019, 2019)

BabyAI: A Platform to Study the Sample Efficiency of Grounded Language Learning - Maxime Chevalier-Boisvert; Dzmitry Bahdanau; Salem Lahlou; Lucas Willems; Chitwan Saharia; Thien Huu Nguyen; Yoshua Bengio (7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019, 2019)

Adversarial Domain Adaptation for Stable Brain-Machine Interfaces - Ali Farshchian; Juan Alvaro Gallego; Joseph Paul Cohen; Yoshua Bengio; Lee E. Miller; Sara A. Solla (7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019, 2019)

Recall Traces: Backtracking Models for Efficient Reinforcement Learning - Anirudh Goyal; Philemon Brakel; William Fedus; Soumye Singhal; Timothy P. Lillicrap; Sergey Levine; Hugo Larochelle; Yoshua Bengio (7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019, 2019)

InfoBot: Transfer and Exploration via the Information Bottleneck - Anirudh Goyal; Riashat Islam; Daniel Strouse; Zafarali Ahmed; Hugo Larochelle; Matthew M. Botvinick; Yoshua Bengio; Sergey Levine (7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019, 2019)

Learning deep representations by mutual information estimation and maximization - R. Devon Hjelm; Alex Fedorov; Samuel Lavoie-Marchildon; Karan Grewal; Philip Bachman; Adam Trischler; Yoshua Bengio (7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019, 2019)

On the Relation Between the Sharpest Directions of DNN Loss and the SGD Step Length - Stanislaw Jastrzebski; Zachary Kenton; Nicolas Ballas; Asja Fischer; Yoshua Bengio; Amos J. Storkey (7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019, 2019)

h-detach: Modifying the LSTM Gradient Towards Better Optimization - Bhargav Kanuparthi; Devansh Arpit; Giancarlo Kerg; Nan Rosemary Ke; Ioannis Mitliagkas; Yoshua Bengio (7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019, 2019)

Modeling the Long Term Future in Model-Based Reinforcement Learning - Nan Rosemary Ke; Amanpreet Singh; Ahmed Touati; Anirudh Goyal; Yoshua Bengio; Devi Parikh; Dhruv Batra (7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019, 2019)

Quaternion Recurrent Neural Networks - Titouan Parcollet; Mirco Ravanelli; Mohamed Morchid; Georges Linarès; Chiheb Trabelsi; Renato De Mori; Yoshua Bengio (7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019, 2019)

Probabilistic Planning with Sequential Monte Carlo methods - Alexandre Piché; Valentin Thomas; Cyril Ibrahim; Yoshua Bengio; Chris Pal (7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019, 2019)

An Empirical Study of Example Forgetting during Deep Neural Network Learning - Mariya Toneva; Alessandro Sordoni; Remi Tachet des Combes; Adam Trischler; Yoshua Bengio; Geoffrey J. Gordon (7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019, 2019)

Deep Graph Infomax - Petar Velickovic; William Fedus; William L. Hamilton; Pietro Liò; Yoshua Bengio; R. Devon Hjelm (7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6-9, 2019, 2019)

Perceptual Generative Autoencoders - Zijun Zhang; Ruixiang Zhang; Zongpeng Li; Yoshua Bengio; Liam Paull (Deep Generative Models for Highly Structured Data, ICLR 2019 Workshop, New Orleans, Louisiana, United States, May 6, 2019, 2019)

State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations - Alex Lamb; Jonathan Binas; Anirudh Goyal; Sandeep Subramanian; Ioannis Mitliagkas; Yoshua Bengio; Michael Mozer (Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA, 2019)

GMNN: Graph Markov Neural Networks - Meng Qu; Yoshua Bengio; Jian Tang (Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA, 2019)

On the Spectral Bias of Neural Networks - Nasim Rahaman; Aristide Baratin; Devansh Arpit; Felix Draxler; Min Lin; Fred A. Hamprecht; Yoshua Bengio; Aaron C. Courville (Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA, 2019)

Manifold Mixup: Better Representations by Interpolating Hidden States - Vikas Verma; Alex Lamb; Christopher Beckham; Amir Najafi; Ioannis Mitliagkas; David Lopez-Paz; Yoshua Bengio (Proceedings of the 36th International Conference on Machine Learning, ICML 2019, 9-15 June 2019, Long Beach, California, USA, 2019)

A Data-Efficient Framework for Training and Sim-to-Real Transfer of Navigation Policies - Homanga Bharadhwaj; Zihan Wang; Yoshua Bengio; Liam Paull (International Conference on Robotics and Automation, ICRA 2019, Montreal, QC, Canada, May 20-24, 2019, 2019)

Interpolation Consistency Training for Semi-supervised Learning - Vikas Verma; Alex Lamb; Juho Kannala; Yoshua Bengio; David Lopez-Paz (Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, IJCAI 2019, Macao, China, August 10-16, 2019, 2019)

Learning Problem-Agnostic Speech Representations from Multiple Self-Supervised Tasks - Santiago Pascual; Mirco Ravanelli; Joan Serrà; Antonio Bonafonte; Yoshua Bengio (20th Annual Conference of the International Speech Communication Association, Interspeech 2019, Graz, Austria, September 15-19, 2019, 2019)

Speech Model Pre-Training for End-to-End Spoken Language Understanding - Loren Lugosch; Mirco Ravanelli; Patrick Ignoto; Vikrant Singh Tomar; Yoshua Bengio (20th Annual Conference of the International Speech Communication Association, Interspeech 2019, Graz, Austria, September 15-19, 2019, 2019)

Learning Speaker Representations with Mutual Information - Mirco Ravanelli; Yoshua Bengio (20th Annual Conference of the International Speech Communication Association, Interspeech 2019, Graz, Austria, September 15-19, 2019, 2019)

InfoMask: Masked Variational Latent Representation to Localize Chest Disease - Saeid Asgari Taghanaki; Mohammad Havaei; Tess Berthier; Francis Dutil; Lisa Di-Jorio; Ghassan Hamarneh; Yoshua Bengio (Medical Image Computing and Computer Assisted Intervention - MICCAI 2019 - 22nd International Conference, Shenzhen, China, October 13-17, 2019, Proceedings, Part VI, 2019)

On Adversarial Mixup Resynthesis - Christopher Beckham; Sina Honari; Vikas Verma; Alex Lamb; Farnoosh Ghadiri; R. Devon Hjelm; Yoshua Bengio; Chris Pal (Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, 2019)

Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input - Maxence Ernoult; Julie Grollier; Damien Querlioz; Yoshua Bengio; Benjamin Scellier (Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, 2019)

Unsupervised State Representation Learning in Atari - Ankesh Anand; Evan Racah; Sherjil Ozair; Yoshua Bengio; Marc-Alexandre Côté; R. Devon Hjelm (Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, 2019)

How to Initialize your Network? Robust Initialization for WeightNorm & ResNets - Devansh Arpit; Víctor Campos; Yoshua Bengio (Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, 2019)

Variational Temporal Abstraction - Taesup Kim; Sungjin Ahn; Yoshua Bengio (Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, 2019)

Gradient based sample selection for online continual learning - Rahaf Aljundi; Min Lin; Baptiste Goujaud; Yoshua Bengio (Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, 2019)

Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics - Giancarlo Kerg; Kyle Goyette; Maximilian Puelma Touzel; Gauthier Gidel; Eugene Vorontsov; Yoshua Bengio; Guillaume Lajoie (Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, 2019)

MelGAN: Generative Adversarial Networks for Conditional Waveform Synthesis - Kundan Kumar; Rithesh Kumar; Thibault de Boissiere; Lucas Gestin; Wei Zhen Teoh; Jose Sotelo; Alexandre de Brébisson; Yoshua Bengio; Aaron C. Courville (Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, 2019)

Wasserstein Dependency Measure for Representation Learning - Sherjil Ozair; Corey Lynch; Yoshua Bengio; Aäron van den Oord; Sergey Levine; Pierre Sermanet (Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada, 2019)

The Benefits of Over-parameterization at Initialization in Deep ReLU Networks - Devansh Arpit; Yoshua Bengio (CoRR, 2019)

Maximum Entropy Generators for Energy-Based Models - Rithesh Kumar; Anirudh Goyal; Aaron C. Courville; Yoshua Bengio (CoRR, 2019)

InfoBot: Transfer and Exploration via the Information Bottleneck - Anirudh Goyal; Riashat Islam; Daniel Strouse; Zafarali Ahmed; Matthew M. Botvinick; Hugo Larochelle; Sergey Levine; Yoshua Bengio (CoRR, 2019)

A Meta-Transfer Objective for Learning to Disentangle Causal Mechanisms - Yoshua Bengio; Tristan Deleu; Nasim Rahaman; Nan Rosemary Ke; Sébastien Lachapelle; Olexa Bilaniuk; Anirudh Goyal; Christopher J. Pal (CoRR, 2019)

Towards Non-saturating Recurrent Units for Modelling Long-term Dependencies - Sarath Chandar; Chinnadhurai Sankar; Eugene Vorontsov; Samira Ebrahimi Kahou; Yoshua Bengio (CoRR, 2019)

Hyperbolic Discounting and Learning over Multiple Horizons - William Fedus; Carles Gelada; Yoshua Bengio; Marc G. Bellemare; Hugo Larochelle (CoRR, 2019)

Learning Dynamics Model in Reinforcement Learning by Incorporating the Long Term Future - Nan Rosemary Ke; Amanpreet Singh; Ahmed Touati; Anirudh Goyal; Yoshua Bengio; Devi Parikh; Dhruv Batra (CoRR, 2019)

Interpolation Consistency Training for Semi-Supervised Learning - Vikas Verma; Alex Lamb; Juho Kannala; Yoshua Bengio; David Lopez-Paz (CoRR, 2019)

Online continual learning with no task boundaries - Rahaf Aljundi; Min Lin; Baptiste Goujaud; Yoshua Bengio (CoRR, 2019)

InfoMask: Masked Variational Latent Representation to Localize Chest Disease - Saeid Asgari Taghanaki; Mohammad Havaei; Tess Berthier; Francis Dutil; Lisa Di-Jorio; Ghassan Hamarneh; Yoshua Bengio (CoRR, 2019)

Wasserstein Dependency Measure for Representation Learning - Sherjil Ozair; Corey Lynch; Yoshua Bengio; Aäron van den Oord; Sergey Levine; Pierre Sermanet (CoRR, 2019)

Towards Standardization of Data Licenses: The Montreal Data License - Misha Benjamin; Paul Gagnon; Negar Rostamzadeh; Chris Pal; Yoshua Bengio; Alex Shee (CoRR, 2019)

Learning Problem-agnostic Speech Representations from Multiple Self-supervised Tasks - Santiago Pascual; Mirco Ravanelli; Joan Serrà; Antonio Bonafonte; Yoshua Bengio (CoRR, 2019)

Reinforced Imitation in Heterogeneous Action Space - Konrad Zolna; Negar Rostamzadeh; Yoshua Bengio; Sungjin Ahn; Pedro O. Pinheiro (CoRR, 2019)

Speech Model Pre-training for End-to-End Spoken Language Understanding - Loren Lugosch; Mirco Ravanelli; Patrick Ignoto; Vikrant Singh Tomar; Yoshua Bengio (CoRR, 2019)

GradMask: Reduce Overfitting by Regularizing Saliency - Becks Simpson; Francis Dutil; Yoshua Bengio; Joseph Paul Cohen (CoRR, 2019)

Compositional generalization in a deep seq2seq model by separating syntax and semantics - Jake Russin; Jason Jo; Randall C. O'Reilly; Yoshua Bengio (CoRR, 2019)

Visualizing the Consequences of Climate Change Using Cycle-Consistent Adversarial Networks - Victor Schmidt; Alexandra Luccioni; S. Karthik Mukkavilli; Narmada Balasooriya; Kris Sankaran; Jennifer T. Chayes; Yoshua Bengio (CoRR, 2019)

GMNN: Graph Markov Neural Networks - Meng Qu; Yoshua Bengio; Jian Tang (CoRR, 2019)

The Journey is the Reward: Unsupervised Learning of Influential Trajectories - Jonathan Binas; Sherjil Ozair; Yoshua Bengio (CoRR, 2019)

N-BEATS: Neural basis expansion analysis for interpretable time series forecasting - Boris N. Oreshkin; Dmitri Carpov; Nicolas Chapados; Yoshua Bengio (CoRR, 2019)

State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations - Alex Lamb; Jonathan Binas; Anirudh Goyal; Sandeep Subramanian; Ioannis Mitliagkas; Denis Kazakov; Yoshua Bengio; Michael C. Mozer (CoRR, 2019)

Non-normal Recurrent Neural Network (nnRNN): learning long time dependencies while improving expressivity with transient dynamics - Giancarlo Kerg; Kyle Goyette; Maximilian Puelma Touzel; Gauthier Gidel; Eugene Vorontsov; Yoshua Bengio; Guillaume Lajoie (CoRR, 2019)

Attention Based Pruning for Shift Networks - Ghouthi Boukli Hacene; Carlos Eduardo Rosar Kós Lassance; Vincent Gripon; Matthieu Courbariaux; Yoshua Bengio (CoRR, 2019)

Updates of Equilibrium Prop Match Gradients of Backprop Through Time in an RNN with Static Input - Maxence Ernoult; Julie Grollier; Damien Querlioz; Yoshua Bengio; Benjamin Scellier (CoRR, 2019)

Do Neural Dialog Systems Use the Conversation History Effectively? An Empirical Study - Chinnadhurai Sankar; Sandeep Subramanian; Christopher J. Pal; Sarath Chandar; Yoshua Bengio (CoRR, 2019)

How to Initialize your Network? Robust Initialization for WeightNorm & ResNets - Devansh Arpit; Victor Campos; Yoshua Bengio (CoRR, 2019)

Learning Powerful Policies by Using Consistent Dynamics Model - Shagun Sodhani; Anirudh Goyal; Tristan Deleu; Yoshua Bengio; Sergey Levine; Jian Tang (CoRR, 2019)

Tackling Climate Change with Machine Learning - David Rolnick; Priya L. Donti; Lynn H. Kaack; Kelly Kochanski; Alexandre Lacoste; Kris Sankaran; Andrew Slavin Ross; Nikola Milojevic-Dupont; Natasha Jaques; Anna Waldman-Brown; Alexandra Luccioni; Tegan Maharaj; et al. (CoRR, 2019)

Conditional Computation for Continual Learning - Min Lin; Jie Fu; Yoshua Bengio (CoRR, 2019)

Interpolated Adversarial Training: Achieving Robust Neural Networks without Sacrificing Accuracy - Alex Lamb; Vikas Verma; Juho Kannala; Yoshua Bengio (CoRR, 2019)

Information matrices and generalization - Valentin Thomas; Fabian Pedregosa; Bart van Merriënboer; Pierre-Antoine Manzagol; Yoshua Bengio; Nicolas Le Roux (CoRR, 2019)